Data Mining and Knowledge Engineering

Rekha B. Venkatapur ¹, V. D. Mytri ², A. Damodaram ³

Affiliations
1 Dept. of CSE, A P S College of Engineering, Bangalore-78, Karnataka, IN
2 GND College of Engineering, Bidar, Karnataka, IN
3 J N T U College of Engineering, Hyderabad, IN

Abstract

Navidgator, an intelligent browsing-tool for image and video data is developed. The main problem with the handling of multimedia databases is the navigation through and the search within the content of a database. The major problem arises from the difference between the possible textual description (annotation) of the database content and its visual appearance. Overcoming the so called semantic gap has been in the focus of research for some time. In the present study, a new system for similarity-based browsing of multimedia databases is presented. The system aims at decreasing the semantic gap by using a tree structure, built up on balanced hierarchical clustering. Using this approach, operators are provided with an intuitive and easy-to-use browsing tool. In the present study an attempt is made is not only on the description of the database organization and retrieval structure, but also how the proposed techniques might be integrated into a single system. In this paper an attempt is made for the direct use of a balanced tree structure for navigating through the database of keyframes, paired with an easy-to-use interface, offering a coarse to fine similarity-based view of the grouped database content.

Keywords

Browsing, Video Databases, Image Databases, Multimedia Retrieval.

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Rekha B. Venkatapur ¹, V. D. Mytri ², A. Damodaram ³

Affiliations
1 Dept. of CSE, A P S College of Engineering, Bangalore-78, Karnataka, IN
2 GND College of Engineering, Bidar, Karnataka, IN
3 JNTU, Hyderabad, IN

Abstract

Digital video libraries are generating tremendous interest in pattern recognition, computer vision, and multimedia research communities. The amount of information currently available in internet and in proprietary databases is increasing every day. In the present study a systematic study is made for the exploration of video sequences. The system, GAMBAL-EVS, segments video sequences extracting an image for each shot and then clusters such images and presents them in a visualization system. The system permits to find similarities between images and to traverse along the video sequences to find the relevant ones.

Keywords

Information Retrieval, Image Retrieval, Clustering of Video Sequences, Video Segmentation.

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